func.func @testAvgPool(%arg0: tensor<256x32x32x3xf32>) -> tensor<256x30x30x16xf32> {
  // CHECK: tac.device = "GPU", tac.inference_type = "FLOAT"
  %0 = "tfl.average_pool_2d"(%arg0) {filter_height = 3 : i32, filter_width = 3 : i32, fused_activation_function = "NONE", padding = "VALID", stride_h = 1 : i32, stride_w = 1 : i32} : (tensor<256x32x32x3xf32>) -> tensor<256x30x30x16xf32>
  func.return %0 : tensor<256x30x30x16xf32>
}

// -----

func.func @main(%arg0: tensor<256x32x32x3xf32>) -> tensor<256x30x30x16xf32> {
  %0 = "tfl.pseudo_const"() {value = dense<1.000000e+00> : tensor<16x3x3x3xf32>} : () -> tensor<16x3x3x3xf32>
  %1 = "tfl.pseudo_const"() {value = dense<1.000000e+00> : tensor<16xf32>} : () -> tensor<16xf32>
  %2 = func.call @fold_all_test(%arg0, %0, %1) : (tensor<256x32x32x3xf32>, tensor<16x3x3x3xf32>, tensor<16xf32>) -> tensor<256x30x30x16xf32>
  func.return %2 : tensor<256x30x30x16xf32>
}

  func.return %rst : tensor<256x30x30x16xf32>

// CHECK: %[[CONSTANT0:.*]] = "tf.Const"() <{value = dense<0.000000e+00> : tensor<3x3x3x16xf32>}>

  func.return %rst : tensor<256x30x30x16xf32>

// CHECK: %[[CONSTANT0:.*]] = "tf.Const"() <{value = dense<0.000000e+00> : tensor<3x3x3x16xf32>}>

  func.return %rst : tensor<256x30x30x16xf32>

// CHECK-DAG: %[[CONSTANT:.*]] = arith.constant dense<0.000000e+00> : tensor<48xf32>
// CHECK-DAG: %[[CONSTANT0:.*]] = arith.constant dense<0.000000e+00> : tensor<1x3x3x48xf32>

  func.return %rst : tensor<256x30x30x16xf32>

// CHECK-DAG: %[[CONSTANT:.*]] = arith.constant dense<0.000000e+00> : tensor<48xf32>
// CHECK-DAG: %[[CONSTANT0:.*]] = arith.constant dense<0.000000e+00> : tensor<1x3x3x48xf32>

  func.return %5 : tensor<256x30x30x16xf32>
}

// CHECK:   func @constWeight(%[[VAL_0:.*]]: tensor<256x32x32x3xf32>) -> tensor<256x30x30x16xf32> {

  %1 = "tfl.relu6"(%0) : (tensor<256x30x30x16xf32>) -> tensor<256x30x30x16xf32>
  func.return %1 : tensor<256x30x30x16xf32>

  // expected-error @+2 {{'tf.Conv2D' op failed to infer returned types}}
  // expected-error @+1 {{op inferred type(s) 'tensor<256x30x30x16xf32>' are incompatible with return type(s) of operation 'tensor<256x32x32x16xf32>'}}
  %0 = "tf.Conv2D"(%arg0, %arg1) {padding = "VALID", strides = [1, 1, 1, 1]} : (tensor<256x32x32x3xf32>, tensor<3x3x3x16xf32>) -> tensor<256x32x32x16xf32>
  func.return %0 : tensor<256x32x32x16xf32>
}

  func.return %0, %1 : tensor<256x32x32x16xf32>, tensor<256x30x30x16xf32>
}

// -----

func.func @testPadding(%arg0: tensor<256x32x32x3xf32>, %arg1: tensor<16x3x3x3xf32>, %arg2: tensor<16xf32>) -> tensor<256x30x30x16xf32> {